LID SPN TRAP

1435703_at

Ubash3b ubiquitin associated and SH3 domain containing, B

AIM Score vs. Gene Expression
Full X range:
Auto X range:
Group Comparisons: Boxplots

CP73

Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)

F-statistic p-value df difference
0.048 0.830 1.0

Model:
AIM ~ expression + C(dose) + expression:C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.665
Model: OLS Adj. R-squared: 0.612
Method: Least Squares F-statistic: 12.56
Date: Thu, 21 Nov 2024 Prob (F-statistic): 9.35e-05
Time: 04:02:33 Log-Likelihood: -100.54
No. Observations: 23 AIC: 209.1
Df Residuals: 19 BIC: 213.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -33.6203 265.956 -0.126 0.901 -590.272 523.031
C(dose)[T.1] 500.2391 486.413 1.028 0.317 -517.834 1518.313
expression 8.7517 26.494 0.330 0.745 -46.701 64.205
expression:C(dose)[T.1] -43.5561 47.538 -0.916 0.371 -143.055 55.943
Omnibus: 0.726 Durbin-Watson: 1.911
Prob(Omnibus): 0.695 Jarque-Bera (JB): 0.666
Skew: 0.365 Prob(JB): 0.717
Kurtosis: 2.599 Cond. No. 1.37e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.650
Model: OLS Adj. R-squared: 0.615
Method: Least Squares F-statistic: 18.56
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.77e-05
Time: 04:02:33 Log-Likelihood: -101.04
No. Observations: 23 AIC: 208.1
Df Residuals: 20 BIC: 211.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 102.1514 219.959 0.464 0.647 -356.676 560.979
C(dose)[T.1] 54.6809 10.710 5.106 0.000 32.340 77.022
expression -4.7773 21.910 -0.218 0.830 -50.480 40.925
Omnibus: 0.502 Durbin-Watson: 1.898
Prob(Omnibus): 0.778 Jarque-Bera (JB): 0.584
Skew: 0.082 Prob(JB): 0.747
Kurtosis: 2.236 Cond. No. 517.

Model:
AIM ~ C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.649
Model: OLS Adj. R-squared: 0.632
Method: Least Squares F-statistic: 38.84
Date: Thu, 21 Nov 2024 Prob (F-statistic): 3.51e-06
Time: 04:02:33 Log-Likelihood: -101.06
No. Observations: 23 AIC: 206.1
Df Residuals: 21 BIC: 208.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 54.2083 5.919 9.159 0.000 41.900 66.517
C(dose)[T.1] 53.3371 8.558 6.232 0.000 35.539 71.135
Omnibus: 0.322 Durbin-Watson: 1.888
Prob(Omnibus): 0.851 Jarque-Bera (JB): 0.485
Skew: 0.060 Prob(JB): 0.785
Kurtosis: 2.299 Cond. No. 2.57

Model:
AIM ~ expression

OLS Regression Results
Dep. Variable: AIM R-squared: 0.194
Model: OLS Adj. R-squared: 0.155
Method: Least Squares F-statistic: 5.041
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0356
Time: 04:02:33 Log-Likelihood: -110.63
No. Observations: 23 AIC: 225.3
Df Residuals: 21 BIC: 227.5
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -526.2992 269.993 -1.949 0.065 -1087.780 35.181
expression 59.5878 26.540 2.245 0.036 4.395 114.781
Omnibus: 1.997 Durbin-Watson: 2.084
Prob(Omnibus): 0.368 Jarque-Bera (JB): 1.290
Skew: 0.308 Prob(JB): 0.525
Kurtosis: 2.017 Cond. No. 428.

CP101

Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)

F-statistic p-value df difference
0.023 0.883 1.0

Model:
AIM ~ expression + C(dose) + expression:C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.510
Model: OLS Adj. R-squared: 0.377
Method: Least Squares F-statistic: 3.820
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0425
Time: 04:02:33 Log-Likelihood: -69.946
No. Observations: 15 AIC: 147.9
Df Residuals: 11 BIC: 150.7
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 401.6559 337.978 1.188 0.260 -342.229 1145.541
C(dose)[T.1] -461.9514 438.523 -1.053 0.315 -1427.135 503.232
expression -37.7689 38.171 -0.989 0.344 -121.783 46.246
expression:C(dose)[T.1] 58.1434 49.910 1.165 0.269 -51.708 167.994
Omnibus: 0.958 Durbin-Watson: 1.022
Prob(Omnibus): 0.619 Jarque-Bera (JB): 0.518
Skew: -0.441 Prob(JB): 0.772
Kurtosis: 2.772 Cond. No. 695.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.450
Model: OLS Adj. R-squared: 0.358
Method: Least Squares F-statistic: 4.905
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0277
Time: 04:02:33 Log-Likelihood: -70.819
No. Observations: 15 AIC: 147.6
Df Residuals: 12 BIC: 149.8
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 100.6955 221.138 0.455 0.657 -381.123 582.513
C(dose)[T.1] 48.5728 16.261 2.987 0.011 13.144 84.002
expression -3.7593 24.956 -0.151 0.883 -58.133 50.614
Omnibus: 2.763 Durbin-Watson: 0.776
Prob(Omnibus): 0.251 Jarque-Bera (JB): 1.901
Skew: -0.851 Prob(JB): 0.387
Kurtosis: 2.624 Cond. No. 251.

Model:
AIM ~ C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.449
Model: OLS Adj. R-squared: 0.406
Method: Least Squares F-statistic: 10.58
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00629
Time: 04:02:34 Log-Likelihood: -70.833
No. Observations: 15 AIC: 145.7
Df Residuals: 13 BIC: 147.1
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 67.4286 11.044 6.106 0.000 43.570 91.287
C(dose)[T.1] 49.1964 15.122 3.253 0.006 16.527 81.866
Omnibus: 2.713 Durbin-Watson: 0.810
Prob(Omnibus): 0.258 Jarque-Bera (JB): 1.868
Skew: -0.843 Prob(JB): 0.393
Kurtosis: 2.619 Cond. No. 2.70

Model:
AIM ~ expression

OLS Regression Results
Dep. Variable: AIM R-squared: 0.041
Model: OLS Adj. R-squared: -0.033
Method: Least Squares F-statistic: 0.5516
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.471
Time: 04:02:34 Log-Likelihood: -74.988
No. Observations: 15 AIC: 154.0
Df Residuals: 13 BIC: 155.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 292.8709 268.411 1.091 0.295 -286.997 872.738
expression -22.7381 30.617 -0.743 0.471 -88.881 43.405
Omnibus: 3.017 Durbin-Watson: 1.538
Prob(Omnibus): 0.221 Jarque-Bera (JB): 1.192
Skew: 0.192 Prob(JB): 0.551
Kurtosis: 1.673 Cond. No. 240.